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The course of Data Visualization is a core course to B. Tech AI students at 4000 level. The course will introduce different data visualization principles and different types of data visualization. The course also complemented with mandatory laboratory work.

The course of social networks is an Elective course at 400 level offered for B. Tech students. The course will introduce the domain of social network analysis and research problems therein. A student will understand the mathematical foundations required for addressing the problems related to social network analysis. Working with the data, algorithms and writing codes are inherent to the course syllabus. Python will be used for the programming language. In Autumn 2022, the course is co-offered alongside CSL7390: Social Network Analysis

The course of social network analysis is an Elective course at 700 level offered for M. Tech, Ph.D. and Final Year B. Tech students. The course will introduce the domain of social network analysis and research problems therein. A student will understand the mathematical foundations required for addressing the problems related to social network analysis. Working with the data, algorithms and writing codes are inherent to the course syllabus. Python will be used for the programming language. In Autumn 2022, the course is co-offered alongside CSL4040: Social Networks

Objective of this course is to learn algorithmic techniques developed for handling large amount of data and emphasize on both theoretical as well as practical aspect of it.

The course of Software Engineering is a core course for B.Tech CSE program. It is a 2000 level course for 2nd year UG. The course will introduce formal methods of software engineering. It will also introduce the modern software engineering to the students.

Objective of this course is to learn algorithmic techniques developed for handling large amount of data and emphasize on both theoretical as well as practical aspect of it.

The course of social network analysis is an Elective course at 700 level offered for M. Tech, Ph.D. and Final Year B. Tech students. The course will introduce the domain of social network analysis and research problems therein. A student will understand the mathematical foundations required for addressing the problems related to social network analysis. Working with the data, algorithms and writing codes are inherent to the course syllabus. Python will be used for the programming language.

Objective of this course is to learn algorithmic techniques developed for handling large amount of data and emphasize on both theoretical as well as practical aspect of it.

The objective of the course is to understand the best practices in software engineering and develop the necessary skills to handle software projects in a principled way.

Objective of this course is to learn different algorithm design techniques, advanced data structures and how to analyze complexity of them.
(Pre-requisite: CS112, CS121, CS222)